The event went really well. The students were very interested in the
workshop. Every student who wants to go to a good grad school is talking about Machine
Learning.
We had a registration of about 8 people, but the turnout was about 20, which was really awesome.
I think the depth we went into, at their level, was alright. However, I feel it could be more structured. Probably a series of 3-4 lectures could achieve that. It would get more people interested as opposed to people coming in for just one lecture and leaving. People their age, coming in for just one session, might not get involved to a serious degree and they won’t care much about it.
With a series of sessions, only the people who are really interested would stay and gain deeper insights. So we could gradually talk about more complex concepts and come up with demonstrations using R or Python to make it illustrative.
We were 3 mentors for 20 people, which was a decent ratio. Also, the university was supportive with laptops and other resources which made it easy for the students to get the exercises done hands-on. The students were very interested and asked a lot of questions. Some of them already had a background and some were just curious, which is a good thing. A student came to me after the workshop seeking suggestions on how he could work around with the data in his project using machine learning. Another one asked my opinion on the statistics side of it. I feel if the students are staying back after the workshop to ask questions, it means they liked it. It showed that it had sparked a bit on interest in them about the topic.
We had a registration of about 8 people, but the turnout was about 20, which was really awesome.
I think the depth we went into, at their level, was alright. However, I feel it could be more structured. Probably a series of 3-4 lectures could achieve that. It would get more people interested as opposed to people coming in for just one lecture and leaving. People their age, coming in for just one session, might not get involved to a serious degree and they won’t care much about it.
With a series of sessions, only the people who are really interested would stay and gain deeper insights. So we could gradually talk about more complex concepts and come up with demonstrations using R or Python to make it illustrative.
We were 3 mentors for 20 people, which was a decent ratio. Also, the university was supportive with laptops and other resources which made it easy for the students to get the exercises done hands-on. The students were very interested and asked a lot of questions. Some of them already had a background and some were just curious, which is a good thing. A student came to me after the workshop seeking suggestions on how he could work around with the data in his project using machine learning. Another one asked my opinion on the statistics side of it. I feel if the students are staying back after the workshop to ask questions, it means they liked it. It showed that it had sparked a bit on interest in them about the topic.
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